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Cantalapiedra, C. P.

Publications and source records attributed to Cantalapiedra, C. P..

3 recordsLinked to original sources

Unveiling the hidden biodiversity of microbial chemoreceptor genes in the rare biosphere

Chemoreception plays a central role in microbial adaptability, influencing both community structure and interactions with the environment. However, many chemosensitive microorganisms occur at low abundances in natural ecosystems, which has limited their detection and study using conventional metagenomic sequencing. Here, we employed a custom-designed target capture sequencing approach--encompassing all known chemoreceptor genes from both cultured and uncultured microorganisms--to uncover and characterize the vast chemosensory potential and biodiversity within the rarest fractions of the microbiome. Compared to standard environmental sequencing methods, our approach enhanced the detection of chemoreceptor (CR) genes and their associated sensing domains by orders of magnitude across diverse environments, including the rhizosphere, phyllosphere, soil, aquatic ecosystems, the human gut, and bovine rumen. This enabled the identification of thousands of low-abundance chemosensitive microorganisms that remained undetectable using conventional sequencing approaches, including known plant pathogens and symbionts. Phylogenetic analysis of the most divergent CR genes revealed evidence for novel chemosensitive species, potentially representing new bacterial phyla and classes. Our study provides a new perspective on the chemoreception capabilities of environmental microbes and opens new avenues for discovering and characterizing novel microbial sensing mechanisms.

microbiology↗

Functional and evolutionary significance of unknown genes from uncultivated taxa

Most microbes on our planet remain uncultured and poorly studied. Recent efforts to catalog their genetic diversity have revealed that a significant fraction of the observed microbial genes are functional and evolutionary untraceable, lacking homologs in reference databases. Despite their potential biological value, these apparently unrelated orphan genes from uncultivated taxa have been routinely discarded in metagenomics surveys. Here, we analyzed a global multi-habitat dataset covering 151,697 medium and high-quality metagenome assembled genomes (MAGs), 5,969 single-amplified genomes (SAGs), and 19,642 reference genomes, and identified 413,335 highly curated novel protein families under strong purifying selection out of previously considered orphan genes. These new protein families, representing a three-fold increase over the total number of prokaryotic orthologous groups described to date, spread out across the prokaryote phylogeny, can span multiple habitats, and are notably overrepresented in recently discovered taxa. By genomic context analysis, we pinpointed thousands of unknown protein families to phylogenetically conserved operons linked to energy production, xenobiotic metabolism and microbial resistance. Most remarkably, we found 980 previously neglected protein families that can accurately distinguish entire uncultivated phyla, classes, and orders, likely representing synapomorphic traits that fostered their divergence. The systematic curation and evolutionary analysis of the unique genetic repertoire of uncultivated taxa opens new avenues for understanding the biology and ecological roles of poorly explored lineages at a global scale.

microbiology↗

eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

bioinformatics↗